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Reverse Engineering of Design Patterns from Java Source Code Nija Shi Ron Olsson UC DAVIS.

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Presentation on theme: "Reverse Engineering of Design Patterns from Java Source Code Nija Shi Ron Olsson UC DAVIS."— Presentation transcript:

1 Reverse Engineering of Design Patterns from Java Source Code Nija Shi Ron Olsson UC DAVIS

2 ASE 2006 Outline Design patterns vs. reverse engineering Reclassification of design patterns Pattern detection techniques PINOT Ongoing and future work

3 UC DAVIS ASE 2006 Design Patterns A design pattern offers guidelines on when, how, and why an implementation can be created to solve a general problem in a particular context. -- Design Patterns: Elements of Reusable Object-Oriented Software Gang of Four (GoF) A few well-known uses –Singleton: Java AWT’s (GUI builder) Toolkit class –Proxy: CORBA’s (middleware) proxy and real objects –Chain of Responsibility: Tomcat’s (application server) request handlers

4 UC DAVIS ASE 2006 Reverse Engineering of Design Patterns Toolkit public static synchronized Toolkit getDefaultToolkit() protected abstract ButtonPeer createButton(Button target) protected abstract TextFieldPeer createTextField(TextField target) protected abstract LabelPeer createLabel(Label target) protected abstract ScrollbarPeer createScrollbar(Scrollbar target) private static Toolkit toolkit; Component TextField Button Label ComponentPeer TextFieldPeerLabelPeer ButtonPeer Container ComponentPeer LayoutManager layoutMgr 1 1 Composite Strategy Bridge AbstractFactory Singleton

5 UC DAVIS ASE 2006 Representative Current Approaches ToolsLanguageTechniquesCase StudyPatterns Targeted SPOOLC++Database query ET++Template Method, Factory Method, Bridge DP++C++Database query DTKComposite, Flyweight, Class Adapter Vokac et al.C++Database query SuperOffice CRMSingleton, Template Method, Observer, Decorator Antoniol et al.C++Software metric Leda, libg++, socket, galib, groff, mec Adapter, Bridge SPQRC++Formal semantic test programsDecorator Balanyi et al.C++XML matching Jikes, Leda, Star Office Calc, Writer Builder, Factory Method, Prototype, Bridge, Proxy, Strategy, Template Method PTIDEJJavaConstraint Solver Java.awt.*,*Composite, Facade FUJABAJavaFuzzy logic and Dynamic analysis Java AWTBridge, Strategy, Composite WoP ScannerJavaAST query AWT, Swing, JDBC API, etc.Abstract Factory HEDGEHOGJavaFormal Semantic PatternBox, Java 1.1, 1.2Most GoF patterns (discussed later) Heuzeroth et al.JavaDynamic analysis Java SwingObserver, Mediator, CoR, Visitor KTSmallTalkDynamic analysis KTComposite, Visitor, Template Method MAISAUMLUML matching Nokia DX200 Switching System Abstract Factory

6 UC DAVIS ASE 2006 Current Approaches Limitations –Misinterpretation of pattern definitions –Limited detection scope on implementation variants Can be grouped as follows: –Targeting structural aspects Analyze class/method declarations Analyze inter-class relationships (e.g., whether one class extends another) –Targeting behavioral aspects Analyze code semantics (e.g., whether a code segment is single entry)

7 UC DAVIS ASE 2006 Targeting Structural Aspects Method –Extract structural relationships (inter-class analysis) –For a pattern, check for certain structural properties Drawback –Relies only on structural relationships, which are not the only distinction between patterns

8 UC DAVIS ASE 2006 Targeting Behavioral Aspects Method –Narrow down search space using inter-class relationships –Verify behavior in method bodies Dynamic analysis Machine learning Static program analysis

9 UC DAVIS ASE 2006 Targeting Behavioral Aspects Drawback –Dynamic analysis: Requires good data coverage Verifies program behavior but does not verify the intent Complicates the task for detecting patterns that involve concurrency –Machine learning: Most patterns have concrete definitions, thus does not solve the fundamental problem.

10 UC DAVIS ASE 2006 if (instance == NULL) instance = new Singleton(); return instance; public class Singleton { private static Singleton instance; private Singleton(){} public static Singleton getInstance() { instance = new Singleton(); return instance; A Motivating Example Detecting the Singleton Pattern: As detected by FUJABA Common search criteria –private Singleton() –private static Singleton instance –public static Singleton getInstance() Problem –No behavioral analysis on getInstance() Solution? } return new Singleton(); Inaccurately recognized as Singleton Correctly identified as a Singleton

11 UC DAVIS ASE 2006 GoF Patterns Reclassified

12 UC DAVIS ASE 2006 Language-provided Patterns Patterns provided in the language or library –The Iterator Pattern “Provides a way to access the elements of an aggregate object sequentially without exposing its underlying representation” [GoF] In Java: –Enumeration since Java 1.0 –Iterator since Java.1.2 –The for-each loop since Java 1.5 –The Prototype Pattern “Specify the kinds of objects to create using a prototypical instance, and create new objects based on this prototype” In Java: –The clone() method in java.lang.Object Pattern Detection –Recognizing variants in legacy code

13 UC DAVIS ASE 2006 Structure-driven Patterns Patterns that are driven by software architecture. Can be identified by inter-class relationships –The Template Method, Composite, Decorator, Bridge, Adapter, Proxy, Facade patterns Inter-class Relationships –Accessibility –Declaration –Inheritance –Delegation –Aggregation –Method invocation

14 UC DAVIS ASE 2006 Behavior-driven Patterns Patterns that are driven by system behavior. Can be detected using inter-class and program analyses. –The Singleton, Abstract Factory, Factory Method, Flyweight, CoR, Visitor, Observer, Mediator, Strategy, and State patterns. Program analysis techniques: –Program slicing –Data-flow analysis –Call trace analysis

15 UC DAVIS ASE 2006 Domain-specific Patterns Patterns applied in a domain-specific context –The Interpreter Pattern “Given a language, define a representation for its grammar along with an interpreter that uses the representation to interpret sentences in the language” [GoF] Commonly based on the Composite and Visitor patterns –The Command Pattern “Encapsulate a request as an object, thereby letting you parameterize clients with different requests, queue or log requests, and support undoable operations” [GoF] A use of combining the Bridge and Composite patterns to separate user interface and actual command execution. The Memento pattern is also used to store a history of executed commands Pattern Detection –Requires domain-specific knowledge

16 UC DAVIS ASE 2006 Generic Concepts Patterns that are generic concepts –The Builder Pattern “Separate the construction of a complex object from its representation so that the same construction can create different representation” [GoF] System bootstrapping pattern, object creation is not necessary –The Memento Pattern “Without violating encapsulation, capture and externalize an object’s internal state so that the object can be restored to this state later” [GoF] Implementation of memo pool and representation of states are not specifically defined. Pattern detection –Lack implementation trace

17 UC DAVIS ASE 2006 Structural aspect –private Singleton() –private static Singleton instance –public static Singleton getInstance() Behavioral aspect –Analyze the behavior in getInstance() Check if lazy-instantiation is implemented –Check if instance is returned –Slice the method body for instance and analyze the sliced program Recognizing the Singleton Pattern recall

18 UC DAVIS ASE 2006 Recognizing the Singleton Pattern public class SingleSpoon { private SingleSpoon(); private static SingleSpoon theSpoon; public static SingleSpoon getTheSpoon() { if (theSpoon == null) theSpoon = new SingleSpoon(); return theSpoon; } Conditions theSpoon == null Statements theSpoon (created) Conditions theSpoon != null Statements theSpoon (returned)

19 UC DAVIS ASE 2006 P attern IN ference and rec O very T ool PINOT –A fully automated pattern detection tool –Designed to be faster and more accurate –Detects structural- and behavioral-driven patterns How PINOT works Source Code Text XMI editors view Pattern Instances UML PINOT J AVA

20 UC DAVIS ASE 2006 Implementation Alternatives Program analysis tools –Extract basic information of the source code Class, method, and variable declarations Class inheritance Method invocations, call trace Variable refers-to and refers-by relationships Parsers –Extract the abstract syntax tree (AST) Compilers –Extract the AST and provide related symbol tables and built-in functions operating on the AST

21 UC DAVIS ASE 2006 Implementation Overview A modification of Jikes (open source C++ Java compiler) Analysis using Jikes abstract syntax tree (AST) and symbol tables Identifying Structure-driven patterns –Considers Java language constructs –Considers commonly used Java utility classes: java.util.Collection and java.util.Iterator Identifying Behavior-driven patterns –Applies data-flow analysis, inter-procedural analysis, alias analysis PINOT considers related patterns –Speed up the process of pattern recognition –E.g., Strategy and State Patterns, CoR and Decorator, etc.

22 UC DAVIS ASE 2006 PINOTHEDGEHOGFUJABA Creational Abstract Factory Yes No Builder Factory Method Yes No Prototype No Singleton Yes Structural Adapter Yes No Bridge Yes Composite Yes No Decorator Yes No Facade Yes Flyweight Yes No Proxy Yes Behavioral Chain of Responsibility YesNo Command Interpreter Iterator YesNo Mediator YesNo Memento No Observer Yes No State YesNo Strategy Yes Template Method Yes Visitor Yes Yes. The tool provides recognition for the pattern and correctly identifies it. No. The tool provides recognition for the pattern but fails to identify it. Blank. The tool does not provide recognition for the pattern.

23 UC DAVIS ASE 2006 Benchmarks Java AWT (GUI toolkit) javac (Sun Java Compiler) JHotDraw (GUI framework) Apache Ant (Build tool) Swing (Java Swing library) ArgoUML (UML editor tool)

24 UC DAVIS ASE 2006 PINOT Results PINOT works well in terms of accuracy: it recognizes many pattern instances in the benchmarks. Like other pattern detection tools, PINOT is not perfect: –False positives Prototype vs. Factory Method –PINOT does not detect Prototype pattern –Prototype pattern involves object creation –PINOT identifies implementation of clone methods as factory methods –False Negatives User-defined data structures –Container structures are commonly used with Observer, Mediator, Composite, Chain of Responsibility patterns, etc.

25 UC DAVIS ASE 2006 Pattern Interpretation Flyweight vs. Immutable –Immutable classes are sharable singletons Mediator vs. Facade –Colleagues of participating in the Mediator pattern can have different types –A mediator class becomes a facade against an individual colleague class

26 UC DAVIS ASE 2006 PINOT Results

27 UC DAVIS ASE 2006 Timing Results A comparison –PtideJ 2-3 hours analyzing JHotDraw Platform: AMD Athlon 2GHz 64b processor –Fujaba 22 minutes analyzing Java AWT Platform: Pentium III 933MHz processor with 1G of memory

28 UC DAVIS ASE 2006 Ongoing and Future Work Investigate other domain-specific patterns –High performance computing (HPC) patterns –Real-time patterns Extend usability of PINOT –Formalize pattern definitions –Visualizing detection results

29 UC DAVIS ASE 2006 PINOT + Eclipse

30 UC DAVIS ASE 2006 Conclusion Reverse engineering of design patterns Reclassifying the GoF patterns for reverse- engineering PINOT – a faster and more accurate pattern detection tool Ongoing and future work More information on our website: /research/pinot

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